Automotive radar sensors are widely used in automated vehicle sensing systems in order to provide information about the surrounding environment to control operation of the automated vehicle and/or to use in Advanced Driver Assistance Systems (ADAS) features. Radar systems may employ a variety of techniques to determine or measure the angle of arrival of a reflected signal. In this way, the angular direction of an object can be estimated. One technique known as Digital Beamforming uses an array of antennas to receive a signal that was reflected by an object. By analyzing the relative phase of the reflected signal across the array of antenna elements the angle from which the signal is received can be determined.
For a MIMO radar system, a receive antenna will receive signals from multiple transmit antennas. For example in a MIMO radar system with two transmit (Tx) antennas and one receive (Rx) antenna, the signals from the two transmit antennas are somehow separated or distinguished upon receiving them to effectively form two receive antenna channels. This concept can be extended to M individual Tx antennas, received by N individual Rx antennas to give an equivalent array of N*M antennas. The positions of the N*M antennas of the equivalent array are just the spatial convolution of the Tx antenna positions and the Rx antenna positions.
Radar systems for fully-automated and semi-automated driving applications that use a Multiple-Input Multiple-Output (MIMO) radar concept with a synthetic-aperture technique from multiple transmit and receive antenna elements have been proposed. This MIMO technique offers a way to synthesize a complex array from a smaller number of transmit and receive antennas. This can be used for various advantages, such as forming a synthetic aperture larger than the physical size of the antenna for improved angle accuracy performance. Another use of MIMO technology is to provide an array with antenna spacing smaller than the physical size of the antennas, for ambiguity benefits. Many other uses and benefits of a MIMO radar design are possible.
In a MIMO Radar system, multiple transmit and receive antennas transmit and receive independent (i.e. orthogonal) radar-signals. The transmitted signals can be considered orthogonal if their cross-correlation along the propagation path is low, approaching zero. There are various methods to transmit and receive orthogonal signal waveforms including Time-Division Multiplexing (TDM), Frequency-Division Multiplexing (FDM), and Phase Modulation (PM). Each of these methods has performance/cost trade-offs.
U.S. Pat. No. 7,474,262 issued to Alland on Jan. 6, 2006 and entitled DIGITAL BEAMFORMING FOR AN ELECTRONICALLY SCANNED RADAR SYSTEM describes a MIMO radar system configured to operate using the TDM method, which results in a maximum degree of orthogonality between signals transmitted from multiple transmit antennas. The detection dynamic range will not be degraded by signal interference between transmitting antennas. However, TDM introduces the ineffective usage of the coherent processing interval (CPI) of the radar measurement. This will degrade the radar's object detection performance by reducing the detection sensitivity (through time multiplexing losses) and the ability to unambiguously measure Doppler across a wide interval (by increasing the time between pulses from a single transmit antenna).
To overcome the performance limitations of the TDM method, it may be desired to generate signals from multiple transmit antennas simultaneously but still separate the signals received simultaneously by each receive antenna to form multiple channels. This requires that multiple signals be generated with some level of orthogonality, transmit from multiple transmit antennas, and the superposition of these signals received by each receive antenna. These signals are then separated after being received. Multiple known methods exist to do this.
One method is Frequency Division Multiplexing. With this method, the transmit signal for each transmit antenna is offset in frequency from the transmit signals for the other transmit antennas. After down-conversion, there will be a frequency offset between the signals from the different Tx antennas. The cost of this approach is that an increased baseband bandwidth is required to sample the signals received from the multiple transmit antennas. Also, the unambiguous range coverage is impacted.
Another method to achieve orthogonality is to implement phase modulation of one transmit signal compared to another. This modulation may involve use of Bi-Phase Modulation with phase states of 0° and 180°, or Poly-Phase Modulation in which more phase states are used. Two classes of phase modulation are used. The first uses regular, periodic codes to shift the received signal in frequency, such as use of a square wave code. The downside of this approach is that the shift in frequency of the received signal from one object can interfere with the signal from another. To avoid this one can, for example, use an increased pulse repetition frequency (PRF) to ensure signals from one transmit antenna do not interfere with another. However, this alternative results in increased system cost and complexity.
Another method of using phase modulation is to modulate the phase of one transmit signal relative to another by, for example, a pseudo-random code. This method is referred to here as Pseudo-Random Phase Modulation (PRPM). By demodulating the received signal according to the transmit code applied to one of the transmit antennas, the signal from that transmit antenna can be recovered. By virtue of the differential phase modulation of the other transmit antennas, the signals from the other transmit antennas are suppressed. The demodulation process can be repeated for the same received signal according to the phase code applied to each transmit antenna. In this method, the composite received signal resulting from the superposition of the signals from multiple transmit antennas can be separated into its individual constituent elements. A limitation of this approach is that, upon demodulation for a given transmit antenna, the energy of the suppressed signals from the other transmit antennas is still present in the recovered signal for the given transmit antenna, but merely distributed across a frequency band.
The distributed energy from the suppressed signals present in the recovered signal is referred to herein as the residue. The residue arises from or is due to the lack of perfect orthogonality between the signals applied to each transmit antenna. The residue present in the recovered signal from a particular transmit antenna consists of the superposition of the individual residues from each of the other transmit antennas. The level or strength of the residue is related to the received signal levels and the degree of orthogonality between the transmit signals. In the case of phase coded waveforms, the cross-correlation of the phase codes used for each transmit antenna determines the degree of orthogonality between the transmit signals and also determines the shape of the frequency spectrum of the residue.
The presence of this residue limits the ability of the radar system to unambiguously extract the signal reflected from a smaller object in the presence of a signal reflected from a larger object. The residue level can be reduced by increasing the orthogonality (i.e. decreasing the cross-correlation) between the phase coded waveforms. A known approach for reducing the residue resulting from PRPM is to increase the phase code length to decrease the residue. However, for some designs, increasing the code length for significant improvement in residue may not be practical or may have cost and performance implications on the system design.
Another approach to reduce the residue has been described in a paper entitled Slow Time Random Phase-Coded Waveforms in MIMO OTHR by Zhiguo Zhao, Jianwen Chen, and Zheng Bao, that was published in the 10th International Symposium on Antennas, Propagation & EM Theory (ISAPE), 2012. In this implementation, a method called Hierarchical Waveform Separation (HWS) is described to reduce the residue from a PRPM MIMO implementation. While this approach may achieve similar performance, it uses a matrix subspace projection method to identify and remove the residue from strong signals. However, its calculation is complex and time-consuming, and generally not practical for low-cost automotive radar.